Today's data centers run a multitude of applications, or “workloads,” that generate I/O. An understanding of the I/O characteristics of an application from various metrics collected is crucial for effective placement of application data to external storage devices and make full use of consolidation advantages that external SAN-based storage has to offer. A lack of such an understanding often leads to application inefficiencies and storage over-provisioning. Many storage admins employ rule-of-thumb and ad hoc techniques for mapping the applications to storage volumes, or logical unit numbers (“LUNs”). In a SAN environment, the LUNs are on storage arrays and different physical storage media in the backend. A popular rule-of-thumb is to mount top-tier applications to an all flash array LUN and lower tier applications to a disk-based LUN. While such methods may work in some deployments, it is not a one-size-fits-all approach. Storage capacity over-provisioning is also a common trend in anticipation of real or perceived performance issues; however, this approach is inefficient and expensive. The applications data volume (LUN) capacity and its placement are decisions that are better guided by detailed application I/O characterization and real time analysis since most applications have a complex mix of I/O patterns. A good understanding of I/O characteristics of applications that use a shared, consolidated storage is critical in designing an efficient storage infrastructure.
Messaging servers (e.g., MS Exchange) and databases (e.g., MS SQL Server) are typical applications that use a SAN for block-based I/O operations. Most of these applications can be further broken down into various components. For example, for SQL components may include database transactions, index access, log write, etc. Each of these components have different I/O patterns and thus need to be supported by different back-end storage devices typically mapped to a separate LUNs.
Some of OS vendors provide tools that can help measure the I/O emanating from each application; however, given the multiple places in the storage stack where this can be measured (e.g., file system layer, block layer, SCSI layer, etc.) the accuracy of the measurement is a concern. Also, in a mixed OS environment, managing multiple diverse OS vendor-provided tools can be a tedious task. In contrast, a SAN network-based tool that can measure I/O characteristics as seen on the wire using a vendor-neutral approach would be most appealing to administrators.